DotMapper: an open source tool for creating interactive disease point maps

BMC Infect Dis. 2016 Apr 12;16:145. doi: 10.1186/s12879-016-1475-5.


Background: Molecular strain typing of tuberculosis isolates has led to increased understanding of the epidemiological characteristics of the disease and improvements in its control, diagnosis and treatment. However, molecular cluster investigations, which aim to detect previously unidentified cases, remain challenging. Interactive dot mapping is a simple approach which could aid investigations by highlighting cases likely to share epidemiological links. Current tools generally require technical expertise or lack interactivity.

Results: We designed a flexible application for producing disease dot maps using Shiny, a web application framework for the statistical software, R. The application displays locations of cases on an interactive map colour coded according to levels of categorical variables such as demographics and risk factors. Cases can be filtered by selecting combinations of these characteristics and by notification date. It can be used to rapidly identify geographic patterns amongst cases in molecular clusters of tuberculosis in space and time; generate hypotheses about disease transmission; identify outliers, and guide targeted control measures.

Conclusions: DotMapper is a user-friendly application which enables rapid production of maps displaying locations of cases and their epidemiological characteristics without the need for specialist training in geographic information systems. Enhanced understanding of tuberculosis transmission using this application could facilitate improved detection of cases with epidemiological links and therefore lessen the public health impacts of the disease. It is a flexible system and also has broad international potential application to other investigations using geo-coded health information.

Keywords: GIS; Tuberculosis; Web interface.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Databases, Factual
  • Female
  • Geographic Information Systems
  • Humans
  • Internet
  • Risk Factors
  • Tuberculosis / epidemiology*
  • User-Computer Interface*